Spending Surge Predicted for Factory Data Management
As big data goes, the industrial sector is among the largest producers, with sensors collecting data along assembly lines on everything from the status of manufacturing equipment to product inspection cameras.
Industrial Internet of Things deployments are therefore expected to boost manufacturers’ already hefty investments in data management and analytics tools as producers seek to up their game from merely collecting to organizing and gleaning insights from industrial data.
That trend is seen pushing industrial spending to new heights. For example, ABI Research last week forecast that manufacturers and industrial firms will spend $19.8 billion in 2026 on data management, data analytics and related digital services. Those investments will target operations ranging from predictive equipment maintenance to production line optimization.
A return on those investments requires upfront planning in terms of priorities, whether the goal is scaling production, improving quality or reducing downtime. Setting priorities also requires closer ties with suppliers, the market researcher said.
“For many manufacturers, there is an appreciation that operational decisions need to be based on empirical evidence rather than guesswork. The challenges are not necessarily capturing and analyzing data, rather what to analyze in the first place,” said Michael Larner, principal analyst at ABI Research. “The findings need to have a meaningful impact on operations and so manufacturers need to take a step back and devise precise objectives.”
Hence, a supplier ecosystem is emerging to help ease manufacturers’ digital transition, or what has become known as Industry 4.0. That transformative approach combines advanced manufacturing techniques with cloud and edge computing, AI and machine learning, robotic process automation and vision systems along with augmented and virtual reality platforms.
Other analysts using roughly the same timeframe as ABI Research report that smart factories that devise workflows for leveraging big data are just around the corner. For example, business consultant Deloitte recently reported that 86 percent of U.S. manufacturers think smart factories will emerge as the main driver of competition by 2025. Meanwhile, 83 percent said the industrial IoT will “transform the way products are made.”
That transformation is being driven in part by the emergence of machine learning tools that allow factory managers to move beyond reporting manufacturing data to recommending actions and predicting outcomes. As big data is democratized, other tools like data visualizations allow production managers to analyze data on the factory floor without the aid of data scientists.
Hence, ABI’s Larner said manufacturers must move beyond mere data collection. “While manufacturers have spent decades refining their physical production lines, today they need to expend effort in optimizing their processes for collecting and analyzing data,” he said.
Another factor shaping the factory of the future is the potential for “re-shoring” manufacturing operations as the novel coronavirus exposes vulnerabilities and reconfigures global supply chains. Among the platforms in the expanding digital production ecosystem are “manufacturing execution systems” designed to help producers manage and leverage IoT data.